能源、环境与空调制冷

１９９７年,世界上１６０多个国家在日本京都签订了有关减少温室气体排放的协议（京都协议）。该协议对缔约国的能源政策甚至经济的发展都有巨大的影响。作为能源消耗量很大的空调制冷行业,有必要对此予以充分的关注和深入研究。本研究了国内外能源环境现状和空调制冷系统与能源环境的关系,给出了对空调制系统适应新的能源结构和环境政策进行适当调整的建议。     

基于相变材料的太阳能PV/T系统性能

利用相变材料（phase change material, PCM）的定温储放热特性,将脂肪酸类PCM填充在装有金属肋片的集热器中,对太阳能光伏（photovoltaic, PV）板进行温度调控,实验分析了不同间歇性热量调控策略下PV/T（photovoltaic/thermal）-PCM系统宏观性能。结果表明：PCM能有效缓解光伏电池的温度波动,但系统运行中PCM的温度分层现象较为严重,制约了其实际利用率;合理的热量调控策略对防止PV/T-PCM系统中光伏电池过热及提升系统性能至关重要,数据显示工况二（调控温度设为45℃,调控时长30 min）和工况三（调控温度设为50℃,调控时长30 min）在调控前后,其光电转换效率分别提升3.4%和2.6%;工况二对应的系统总效率为90.8%,工况三为84.45%,均在工况一（无调控）的基础上有显著提升。     

Modeling of annular reactors with surface reaction using computational fluid dynamics (CFD)

A CFD-based model for predicting the performance of annular reactors with surface reaction was developed. The capability of several hydrodynamic models to predict successfully the kinetic behavior of the reactor under diffusion limiting conditions was assessed against experimental data. The evaluation included five models: laminar, standard k–ε, realizable k–ε, Reynolds stress (RSM), and Abe–Kondoh–Nagano (AKN). The catalytic decomposition of hydrogen peroxide over a Mn/Al oxide catalyst coated on the reactor surface was used as a model reaction. The reactor was tested within a range of flow rates corresponding to 530<Re<11,000 and intrinsic reaction rate constants of 5×10^?5 to 1 m/s. The results demonstrated that the performance of the hydrodynamic models is associated with their capability to predict external mass transfer and ultimately, the level of mass transfer limitation present in the reacting system. For laminar flow conditions, the laminar model is capable of predicting the experimental behavior of the system. For transient and turbulent flow regimes, all the analyzed turbulence models provided good predictions of the system when the process was controlled by surface reaction. When the system presented some degree of mass transfer limitation, AKN and RSM exhibited better performance.     

Convective heat transfer prediction in large rectangular cross-sectional area Earth-to-Air Heat Exchangers

An Earth-to-Air Heat Exchanger (ETAHE) uses the ground's thermal storage capacity to dampen ambient air temperature oscillations by delivering the outdoor air to the indoors through a horizontally buried duct. With their lower airflow resistance, large cross-sectional area ETAHEs have been found to be more energy efficient than the conventional small ones, especially when integrated in hybrid ventilation systems. However, the lack of available methods for determining the heat convection at the duct surfaces has made accurate energy simulation and proper system design overly difficult. In this study, numerical experiments using computational fluid dynamics (CFD) were conducted to investigate the airflow and thermal behavior in the large ducts. A two-layer turbulence model was used to ensure accuracy in resolving the flow information in the near-wall region, which is critical for predicting accurate heat convection. The modeling method was verified by comparing its results with measurements from literature. Parametric studies were conducted to identify the influential design and operation variables for the heat convection. Thirty numerical experimental setups designed with the Latin Hypercube Sampling method were simulated to prepare a database with six design parameters as the simulation inputs and average Nusselt numbers over the duct ceiling, wall, and floor as the outputs. Based on the database an artificial neural network (ANN) model was trained to build a mathematical relation between the design variables and the Nusselt numbers. The developed ANN model showed very accurate prediction when compared with test data.     

An effective hybrid multi-objective genetic algorithm for bi-criteria scheduling on a single batch processing machine with non-identical job sizes

This paper addresses the problem of scheduling jobs with non-identical sizes on a single batch processing machine. A batch processing machine is one which can process multiple jobs simultaneously as a batch as long as the total size of jobs being processed does not exceed the machine capacity. The batch processing time is equal to the longest processing time among all jobs in the batch. For the simultaneous minimization of the bi-criteria of makespan and maximum tardiness, we propose two different multi-objective genetic algorithms based on different representation schemes. While the first algorithm do search via generating sequences of jobs using genetic operators and then batching jobs keeping their order in the sequence, the second algorithm uses the idea of generating batches of jobs directly using genetic operators and ensures feasibility through using heuristic procedures. The type of representation used in the second algorithm allows introducing heuristics with the ability of biasing the search towards each objective and also allows hybridization with a local search heuristic that gives the ability of finding Pareto-optimal or locally efficient Pareto-solutions. Computational results show that the non-dominated solutions obtained by the latter algorithm are very superior in closeness to the true Pareto-optimal solutions and to keep diversity in the obtained Pareto-set, as the problem size increases.     

A Simulated Annealing algorithm for a mixed model assembly U-line balancing type-I problem considering human efficiency and Just-In-Time approach

This research deals with balancing a mixed-model U-line in a Just-In-Time (JIT) production system. The research intends to reduce the number of stations via balancing the workload and maximizing the weighted efficiency, which both are considered as the objectives of this research paper.After balancing the line and determining the number of stations, the labor assignment policy should be set. In this study, it was assumed that there are two types of operators: permanent and temporary. Both types can work in regular and overtime periods. Based on their skill levels, workers are classified into four types. The sign at each work station indicates types of workers allowed to work at that station. An alert system using the hybrid kanban systems was also considered. To solve this problem, a Simulated Annealing algorithm was applied in the following three stages. First, the balancing problem was solved and the number of stations was determined. Second, workers were assigned to the workstations in which they are qualified to work. Following that, an alert system based on the kanban system was designed to balance the work in the process inventory. This was achieved by defining control points based on the processing time and making control decisions to minimize the number of kanban cards. In the proposed SA algorithm, two methods for the temperature cooling schedule were considered and two methods were defined for determining the number of neighborhood search. The initial temperature was considered equal to the cost of the initial solution to reach the convergence situation as soon as possible. Five problems were solved in small size using the GAMS software. The results obtained from the GAMS software were compared with those obtained from the SA algorithm to determine the performance difference. The computational results demonstrated that the SA algorithm is more consistent with the answers obtained. Also seven large scale problems were solved. The results showed that the SA algorithm still have better reliability. To show the efficiency of the proposed SA algorithm, an axel assembly company was studied. To satisfy demands and reduce backlogging, a mixed model assembly line was designed for this case study. The results showed that the mixed model assembly line designed using the SA algorithm had good efficiency.     

A hybrid multi-objective approach based on the genetic algorithm and neural network to design an incremental cellular manufacturing system

One important issue related to the implementation of cellular manufacturing systems (CMSs) is to decide whether to convert an existing job shop into a CMS comprehensively in a single run, or in stages incrementally by forming cells one after the other, taking the advantage of the experiences of implementation. This paper presents a new multi-objective nonlinear programming model in a dynamic environment. Furthermore, a novel hybrid multi-objective approach based on the genetic algorithm and artificial neural network is proposed to solve the presented model. From the computational analyses, the proposed algorithm is found much more efficient than the fast non-dominated sorting genetic algorithm (NSGA-II) in generating Pareto optimal fronts.     

A rapid and sensitive method for separation of Cu2+ ions from industrial wastewater sample and water samples with methacrylamide‐ethylene glycol dimethacrylate: A new synthesis of molecularly imprinted polymer

In this study, new molecularly imprinted polymer particles (MIP) were synthesised to extract Cu²⁺ ions from aqueous solutions using radical polymerisation. MIP was developed using the methacrylamide‐ethylene glycol dimethacrylate (EGDMA) cross linking agent, methacrylamide monomer, and ACV initiator by the radical polymerisation method. A comparison of various cross linking agents in MIP production showed that the best cross linking agents are EGDMA and gallic acid. The template ions were removed by leaching with 0.100 M HCl. The polymer particles were characterised by FTIR spectroscopy, thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The effect of different parameters such as cross linkers, pH, time, maximum adsorption capacity, and kinetic and isotherm adsorption were investigated. The best conditions were determined (pH = 8.0, t = 10 min, and q _m  = 262.53 mg g⁻¹). The adsorption data were best fitted by Freundlich isotherm and pseudo second order kinetic models, as well. Due to its high adsorption capacity and multi‐layer behaviour, this method is an easy, fast and safe way to extract cations. Removal of Cu²⁺ in certified tap water and rain water was demonstrated and the industrial wastewater sample (Charmshahr, Iran) with which the MIP was developed using Methacrylamide‐ Ethylene Glycol Dimethacrylate (EGDMA) was good enough for Cu²⁺ determination in matrices containing components with similar chemical property such as Co²⁺, Zn²⁺, Fe².